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Zhenfang Wang

4 papers hereh-index 28 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.LG1
  • cs.SD1
same name
  • Zhenfang Wang — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedOmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.SD2026

JoyAI-Talker: Full-Duplex Speech Interactive Large Model Built for Empathetic Voice Agents

Yinhao Bai, Jinming Chen, Yafeng Chen +26

We present JoyAI-Talker, a full-duplex speech dialogue system that delivers robust foundation model capabilities while empowering empathetic interaction and voice agent intelligenc…

cs.CL2026

JoyAI-LLM Flash: Advancing Mid-Scale LLMs with Token Efficiency

Aichen Cai, Anmeng Zhang, Anyu Li +66

We introduce JoyAI-LLM Flash, an efficient Mixture-of-Experts (MoE) language model designed to redefine the trade-off between strong performance and token efficiency in the sub-50B…

cs.CL2025

Beyond Token Length: Step Pruner for Efficient and Accurate Reasoning in Large Language Models

Canhui Wu, Qiong Cao, Chang Li +5

Large Reasoning Models (LRMs) demonstrate strong performance on complex tasks but often suffer from excessive verbosity, known as "overthinking." Existing solutions via reinforceme…

cs.LG2023★ 1 cited

OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System

Chao Xue, Wei Liu, Shuai Xie +25

Automated machine learning (AutoML) seeks to build ML models with minimal human effort. While considerable research has been conducted in the area of AutoML in general, aiming to t…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.